Food Systems, Safety & Sustainability (FSSS) supports responsible access to the data, code, materials, protocols, and other research outputs underlying published findings.

Authors must provide a Data Availability Statement for every research manuscript and for any other article containing original data, secondary data analysis, computational analysis, systematic evidence synthesis, or reusable research materials.

Data supporting published results should be deposited in a trusted repository and made publicly accessible wherever this is legally, ethically, contractually, culturally, and technically possible. Where public sharing is not possible, authors must explain the restriction clearly and describe whether qualified researchers may obtain controlled access.

Data sharing must not compromise participant privacy, informed consent, Indigenous or community data governance, commercial confidentiality, intellectual-property rights, food-system security, biosecurity, legal obligations, or legitimate third-party restrictions.

1. Purpose of This Policy

This policy is intended to:

• improve the transparency and reliability of published research;
• permit verification of reported results where appropriate;
• support responsible reuse of research outputs;
• improve reproducibility and methodological assessment;
• ensure that data restrictions are explained transparently;
• recognise legitimate ethical, legal, cultural, commercial, and security limits on sharing;
• encourage proper citation and credit for data creators;
• reduce unnecessary duplication of data collection;
• support long-term preservation of scholarly outputs; and
• maintain the integrity of the published scholarly record.

2. Scope

This policy applies to data and related materials associated with:

• Original Research Articles;
• Systematic Reviews and Meta-Analyses;
• Scoping Reviews;
• Methods Papers;
• Data Papers;
• Short Communications;
• Case Studies;
• Policy Analyses containing original or secondary data;
• qualitative and mixed-methods research;
• laboratory and experimental research;
• observational and survey research;
• life-cycle assessments and environmental-footprint studies;
• economic evaluations;
• mathematical, statistical, and computational modelling;
• artificial-intelligence and machine-learning studies;
• geospatial and remote-sensing research;
• secondary analysis of existing datasets; and
• other articles whose findings depend on identifiable research data, code, or materials.

3. Definition of Research Data

For the purposes of this policy, research data include recorded factual material, observations, measurements, responses, outputs, or evidence necessary to support, verify, reproduce, or understand the reported findings.

Research data may include:

• numerical datasets;
• laboratory measurements;
• survey responses;
• interview and focus-group transcripts;
• qualitative codes and coding frameworks;
• field notes and observational records;
• food-safety surveillance records;
• microbiological, chemical, nutritional, or toxicological measurements;
• environmental and agricultural monitoring data;
• economic and supply-chain data;
• administrative and registry data;
• geospatial and remote-sensing data;
• photographs, audio, video, and image data;
• model inputs and outputs;
• simulation results;
• software source code and analytical scripts;
• machine-learning training, validation, and test data;
• AI prompts, configuration information, and relevant outputs;
• systematic-review search results and extraction data;
• data dictionaries, codebooks, ontologies, and metadata;
• protocols, questionnaires, interview guides, and instruments; and
• other materials required to evaluate the reported results.

4. Data Underlying Published Findings

Authors should make available the minimum data necessary to reproduce or verify all material results reported in the article.

The shared package should ordinarily include, where applicable:

• the data underlying tables and figures;
• data supporting principal and secondary outcomes;
• the final analytical dataset;
• information explaining exclusions and missing data;
• data dictionaries and variable definitions;
• units of measurement and coding conventions;
• statistical or computational scripts;
• software and package versions;
• model parameters and assumptions;
• quality-control and validation information;
• README documentation;
• licensing and access information; and
• other information necessary for responsible interpretation and reuse.

Authors are not required to share every record collected during a project where those records do not support the published article or cannot be shared lawfully or ethically.

5. Data Availability Statement

Every applicable manuscript must contain a separate section titled Data Availability.

The statement must explain:

• whether data were generated or analysed;
• whether the supporting data are publicly available;
• the name of the repository;
• the DOI, accession number, handle, or other persistent identifier;
• which data and related materials are available;
• the applicable licence or reuse conditions;
• any embargo period;
• any ethical, legal, contractual, cultural, commercial, or security restriction;
• whether controlled access is possible;
• the procedure and criteria for requesting access;
• the person, committee, institution, or repository responsible for access decisions; and
• the expected period during which access will remain available.

Statements such as “data are available,” “data are confidential,” or “data are available upon request” are insufficient without additional explanation.

6. Preferred Data-Sharing Standard

Authors should deposit data in a trusted disciplinary, institutional, governmental, or general-purpose repository before final acceptance.

Data should be:

• assigned a persistent identifier;
• described using sufficient metadata;
• stored in non-proprietary or widely accessible formats where possible;
• accompanied by documentation necessary for interpretation;
• linked clearly to the published article;
• licensed for reuse where lawful and appropriate;
• versioned where changes may occur;
• preserved for long-term access; and
• managed according to relevant disciplinary standards.

Authors are encouraged to manage data consistently with the FAIR principles of findability, accessibility, interoperability, and reusability.

7. Trusted Repositories

A suitable repository should normally provide:

• persistent identifiers;
• publicly accessible metadata;
• long-term preservation arrangements;
• clear access and reuse conditions;
• version control or change records;
• data-integrity and security measures;
• controlled-access functions where required;
• citation information; and
• a stable institutional or organisational basis.

Authors should prefer a recognised disciplinary repository where one is available. Suitable general-purpose repositories may be used where no appropriate disciplinary repository exists.

Examples may include:

• Zenodo;
• Dryad;
• Figshare;
• Dataverse repositories;
• Open Science Framework;
• institutional repositories;
• government data repositories;
• domain-specific agricultural, genomic, environmental, social-science, or public-health repositories; and
• other repositories providing equivalent preservation and access functions.

Reference to a repository does not constitute endorsement by FSSS or Panorama Scholarly Group.

8. Unsuitable Data Locations

The following should not normally be used as the sole long-term location for supporting research data:

• personal websites;
• temporary file-transfer services;
• personal cloud-storage folders;
• email attachments;
• commercial links without preservation guarantees;
• private laboratory servers without an access plan;
• social-media platforms;
• unversioned collaborative documents;
• links that require an unidentified personal account; or
• services that may delete files automatically.

Code-hosting platforms may be used for software development, but an archived release with a persistent identifier should be created where the code supports the published results.

9. Timing of Data Deposit

Data should normally be deposited before final acceptance so that:

• editors can verify the Data Availability Statement;
• reviewers can be granted confidential access where appropriate;
• persistent identifiers can be included in the article;
• documentation deficiencies can be corrected before publication; and
• the dataset can become accessible no later than publication of the article.

During double-anonymous peer review, authors may provide an anonymised private repository link or another secure access mechanism that does not reveal author identity.

10. Embargoes

A temporary embargo may be accepted where it is required by:

• a repository or funder policy;
• an ethical or legal obligation;
• a legitimate intellectual-property process;
• a formal data-use agreement;
• protection of participants or communities;
• a reasonable period for completing a related primary analysis; or
• another documented and proportionate reason.

The Data Availability Statement must identify the reason for the embargo, the date on which it is expected to end, and the access procedure during the embargo where applicable.

Indefinite or unexplained embargoes are not consistent with this policy.

11. Data Citation

Datasets supporting the article must be cited formally where they are publicly accessible or possess a stable identifier.

A dataset citation should include:

• the creator or responsible organisation;
• the year;
• the dataset title;
• the resource type;
• the repository;
• the version where applicable; and
• the DOI or persistent identifier.

PSG Format example:

Lee, Sungho, and Maria Weber. 2026. Household Food-Safety and Sustainable Consumption Survey Data. Data set. Zenodo. Version 1. https://doi.org/10.xxxx/xxxxx

In-text citation: (Lee and Weber 2026)

Merely mentioning a repository link in the Data Availability Statement does not replace formal citation where the dataset is a distinct research output.

12. Licensing and Reuse

Authors should apply a clear data licence where they possess the authority to do so.

The licence should explain whether users may:

• copy and redistribute the data;
• adapt or transform the data;
• use the data commercially;
• combine the data with other sources;
• redistribute modified versions; and
• reuse the data subject to attribution or other conditions.

The Creative Commons licence applied to the journal article does not automatically apply to every associated dataset, software package, third-party resource, or supplementary file. Authors must identify applicable rights separately.

Data must not be licensed more openly than permitted by participant consent, third-party rights, community governance, contracts, law, or ethical approval.

13. Metadata and Documentation

Shared data must be accompanied by documentation sufficient for a qualified researcher to understand and use the resource responsibly.

Documentation should include, where applicable:

• a README file;
• dataset title and description;
• creator and contributor information;
• collection dates and locations at an appropriate level of precision;
• sampling and recruitment procedures;
• variable names and definitions;
• coding schemes;
• units of measurement;
• missing-value conventions;
• data-cleaning and transformation procedures;
• software requirements;
• file relationships;
• version information;
• known errors and limitations;
• ethical and access restrictions;
• licensing information; and
• recommended citation.

14. Data Formats

Authors should use durable, widely recognised, and machine-readable formats where possible.

Examples may include:

• CSV or TSV rather than proprietary spreadsheet formats;
• TXT, XML, JSON, or other documented structured formats;
• TIFF or another appropriate archival image format;
• standard geospatial formats with coordinate-reference information;
• documented statistical formats where conversion would cause loss of information;
• plain-text source code;
• open and documented model-exchange formats; and
• discipline-specific community standards.

Proprietary formats may be included where scientifically necessary, but authors should also provide an accessible alternative where reasonably possible.

15. Analytical Code and Software

Code used to generate published results should be shared wherever legally and technically possible.

Shared code should include:

• scripts used for data cleaning and transformation;
• statistical-analysis code;
• model-development and validation code;
• figure- and table-generation scripts;
• software version information;
• package dependencies;
• configuration files;
• random seeds where applicable;
• instructions for execution;
• example input and output where useful;
• licensing information; and
• known limitations.

Authors must not share confidential credentials, access tokens, passwords, personal data, unsafe code, or other restricted information.

16. Research Materials and Protocols

Where relevant, authors should make available materials necessary to understand or reproduce the research, including:

• study protocols;
• statistical analysis plans;
• questionnaires and survey instruments;
• interview and focus-group guides;
• coding frameworks;
• laboratory procedures;
• standard operating procedures;
• model specifications;
• data-extraction forms;
• search strategies;
• consent materials where lawful and appropriate;
• calibration and validation documentation; and
• other reusable methodological resources.

Copyrighted or licensed instruments should not be redistributed without permission. Authors should instead identify the source, licence, and lawful access procedure.

17. Supplementary Files

Small supporting datasets, codebooks, questionnaires, or additional tables may be submitted as supplementary files.

A dedicated repository is preferred where:

• the data are large or complex;
• independent citation is appropriate;
• versioning is required;
• long-term preservation is important;
• controlled access is necessary;
• the resource may be reused independently; or
• the file format is unsuitable for the journal platform.

Supplementary files are subject to editorial and peer review. Authors remain responsible for their accuracy, legality, documentation, accessibility, and anonymisation.

18. Personal and Sensitive Data

Authors must not publicly share identifiable personal information unless:

• the sharing is ethically justified;
• participants provided valid consent for the specific disclosure;
• the sharing complies with applicable law;
• the relevant ethics committee approved the procedure; and
• the scholarly need outweighs the privacy risk.

Sensitive data may include:

• names and contact information;
• health and genetic information;
• biometric or behavioural information;
• precise geographical information;
• employment and financial records;
• dietary, cultural, religious, or community information;
• interview transcripts;
• photographs, audio, or video;
• commercially sensitive farm or business records; and
• combined variables that create a re-identification risk.

19. Anonymisation and De-Identification

Before sharing participant-level data, authors must evaluate whether the data have been anonymised or de-identified adequately.

Authors should consider:

• direct identifiers;
• indirect identifiers;
• rare combinations of characteristics;
• small geographical areas;
• dates and event sequences;
• free-text fields;
• images, audio, and video;
• linkage with publicly available datasets;
• the size and characteristics of the study population; and
• the possibility of future re-identification.

Removal of names alone does not necessarily constitute adequate anonymisation.

Where anonymisation would destroy the scientific value of the data or cannot reduce risk sufficiently, controlled access should be used.

20. Controlled Access

Controlled access is appropriate where data cannot be made openly available but may be shared with qualified researchers under defined conditions.

A controlled-access process should identify:

• the person, committee, institution, or repository responsible for decisions;
• who may apply;
• the purposes for which access may be granted;
• the documentation required;
• ethical or institutional approvals required from applicants;
• data-security requirements;
• the form of the data-use agreement;
• restrictions on redistribution or re-identification;
• the expected decision timeframe;
• whether access fees apply; and
• the period for which the access mechanism will be maintained.

Access criteria should be reasonable, transparent, non-discriminatory, and consistent with the original consent and governance requirements.

21. Data Available upon Reasonable Request

The statement “available from the corresponding author upon reasonable request” should be used only where repository deposit or formal controlled access is not reasonably possible.

The statement must explain:

• why public repository deposit is not possible;
• what data are available;
• who may request access;
• the permitted purposes;
• the required approvals or agreements;
• who will assess the request;
• the expected response period; and
• any lawful grounds on which access may be declined.

Authors must respond to legitimate requests consistently and in good faith. Personal disagreement, academic competition, nationality, institutional status, or anticipated criticism is not an appropriate reason to deny access.

Where continued access would depend entirely on one individual author, institutional or repository-based management is strongly preferred.

22. Third-Party Data

Authors may publish research based on data obtained from governments, companies, repositories, institutions, organisations, or other third parties.

The Data Availability Statement must identify:

• the data owner or provider;
• how the authors obtained access;
• the applicable licence or agreement;
• whether the authors are authorised to redistribute the data;
• where other qualified researchers may apply for access;
• whether the authors received privileged access; and
• any restrictions affecting reproducibility.

The journal does not require authors to violate a valid third-party agreement. However, the access conditions must be described transparently, and the research must remain sufficiently verifiable for publication.

23. Commercially Confidential Data

Commercial confidentiality may justify restricted access but does not remove the obligation to describe the supporting evidence and the nature of the restriction.

Authors should disclose:

• the organisation controlling the data;
• the reason for confidentiality;
• whether the sponsor can prevent publication;
• whether the authors had complete access to the data;
• whether the authors conducted the analysis independently;
• whether an independent researcher may apply for access;
• whether aggregated or de-identified data can be shared; and
• how long the restriction is expected to remain.

A manuscript may be unsuitable for publication where contractual restrictions prevent authors from verifying the data, reporting unfavourable findings, responding to editorial questions, or supporting the published conclusions.

24. Food-System Security and Biosecurity

Public sharing may be restricted where data could create a substantial risk to food safety, public health, agriculture, animals, communities, critical infrastructure, or the environment.

Potentially sensitive material may include:

• specific vulnerabilities in food-production or distribution systems;
• security arrangements at food or water facilities;
• methods for evading contamination detection;
• locations or inventories of hazardous biological or chemical materials;
• information facilitating intentional contamination;
• detailed pathogen-enhancement procedures;
• precise locations of vulnerable ecological or agricultural resources;
• commercial supply-chain security information; and
• other information presenting a credible misuse risk.

Restrictions must be proportionate. Authors should share non-sensitive metadata, aggregated results, redacted data, or a controlled-access version where possible.

25. Indigenous, Traditional, and Community-Governed Data

Research involving Indigenous peoples, traditional knowledge, local ecological knowledge, community-held information, biological resources, culturally sensitive data, or collective rights must respect applicable data-sovereignty and governance requirements.

Authors should consider:

• collective as well as individual consent;
• community authority over access and reuse;
• culturally appropriate metadata;
• rights to control, possess, and benefit from data;
• restrictions on commercial or external reuse;
• appropriate attribution and benefit sharing;
• community-approved repositories;
• local governance protocols;
• risks of exploitation, stigmatisation, or misappropriation; and
• the CARE Principles for Indigenous Data Governance where relevant.

Open-data expectations do not override Indigenous or community rights, valid governance processes, or culturally grounded restrictions.

26. Qualitative Research Data

Qualitative data require particular attention because complete transcripts, recordings, field notes, and quotations may permit identification even after names have been removed.

Authors should evaluate:

• the consent provided by participants;
• the sensitivity of the subject matter;
• the size and identifiability of the community;
• the presence of personal narratives;
• risks to participants and third parties;
• cultural and contextual information;
• the possibility of deductive disclosure;
• ethical restrictions on secondary use; and
• whether controlled access or partial sharing is appropriate.

Where full transcripts cannot be shared, authors may provide, where appropriate:

• an interview guide;
• a coding framework;
• a de-identified excerpt set;
• aggregated thematic data;
• analytic memos;
• a detailed description of the analysis;
• controlled access to selected material; or
• another resource supporting methodological transparency.

27. Clinical Trials and Interventional Studies

Reports of clinical trials or comparable participant-level interventions must contain a data-sharing statement consistent with the registered data-sharing plan.

The statement should specify:

• whether de-identified individual participant data will be shared;
• which participant data will be shared;
• whether a data dictionary will be available;
• whether the protocol, statistical analysis plan, consent form, analytic code, or other documents will be shared;
• when access will begin;
• how long access will remain available;
• who may obtain access;
• the permitted types of analysis;
• the procedure for submitting a request;
• the criteria used to evaluate requests;
• whether a data-use agreement is required; and
• the repository or access mechanism.

Material changes to the registered data-sharing plan must be disclosed in the manuscript and updated in the relevant trial registry where possible.

28. Systematic Reviews and Evidence Syntheses

Systematic reviews, meta-analyses, and scoping reviews should make available the materials necessary to evaluate and update the review.

These may include:

• complete search strategies;
• database and platform information;
• search dates;
• deduplicated search records;
• screening decisions;
• full-text exclusion reasons;
• data-extraction forms;
• extracted data;
• risk-of-bias assessments;
• certainty-of-evidence assessments;
• meta-analysis code;
• effect-size calculations;
• analysis files; and
• the review protocol and amendments.

Redistribution of copyrighted full-text publications is not permitted unless authorised. Authors may instead provide bibliographic records and lawful links.

29. Artificial Intelligence and Machine Learning

AI and machine-learning studies should make available sufficient information to assess the model and reproduce the analysis where possible.

Relevant materials may include:

• training, validation, and test-data descriptions;
• eligibility and exclusion criteria;
• data provenance;
• preprocessing and feature-engineering procedures;
• model architecture and configuration;
• hyperparameters;
• software and package versions;
• random seeds;
• training and evaluation code;
• model weights where legally and technically possible;
• performance and calibration outputs;
• subgroup and fairness analyses;
• prompts and system instructions where relevant;
• human-oversight procedures; and
• documentation of proprietary or inaccessible components.

Where the underlying data or model cannot be shared, authors must describe the restriction and provide the maximum level of methodological transparency reasonably possible.

30. Geospatial and Environmental Data

Geospatial, ecological, agricultural, fisheries, biodiversity, and remote-sensing data may require restricted precision where public disclosure could:

• identify individual farms or businesses;
• expose participant or community locations;
• threaten endangered species or protected habitats;
• reveal sensitive infrastructure;
• create security or biosecurity risks;
• violate licence conditions; or
• enable harmful exploitation of natural resources.

Authors should consider sharing generalised coordinates, spatially aggregated data, masked locations, reduced-resolution datasets, or controlled-access records.

Coordinate-reference systems, spatial resolution, processing methods, and masking procedures should be documented.

31. Data Papers

Data Papers must normally provide public access to the dataset described by the article.

A Data Paper should include:

• a persistent dataset identifier;
• complete metadata;
• a clear data licence;
• collection and processing methods;
• quality-assurance procedures;
• file and variable descriptions;
• known limitations;
• recommended reuse conditions;
• version information;
• preservation information; and
• an explanation of any restricted component.

A manuscript may not be suitable as a Data Paper where the principal dataset is inaccessible without sufficient ethical, legal, cultural, security, or contractual justification.

32. Data Integrity

Data shared in connection with an article must correspond accurately to the research described in the manuscript.

Authors must not:

• fabricate or falsify data;
• substitute unrelated data;
• remove inconvenient observations without disclosure;
• alter shared data after peer review without version documentation;
• share selectively modified data that cannot reproduce the published results;
• misrepresent synthetic data as empirical data;
• conceal relevant missingness or exclusions;
• provide unusable or deliberately incomplete files;
• claim that data are available when they are not; or
• provide a false repository, DOI, access procedure, or data owner.

33. Data Review during Peer Review

Editors and reviewers may request access to supporting data, code, or materials where necessary to evaluate:

• the accuracy of reported results;
• the suitability of the analytical method;
• the consistency of figures and tables;
• the treatment of missing data or exclusions;
• the validity of a model or computational result;
• image or data-integrity concerns;
• the reproducibility of principal analyses; or
• another material methodological or ethical question.

Confidential data should be provided through a secure and authorised mechanism. Reviewers must comply with the journal’s confidentiality and data-protection requirements.

Failure to provide relevant supporting material may affect the editorial decision where the reliability of the manuscript cannot otherwise be established.

34. Reasonable Restrictions during Peer Review

Authors may explain that certain data cannot be supplied directly to reviewers because of:

• participant-consent limitations;
• privacy or data-protection law;
• third-party ownership;
• commercial confidentiality;
• Indigenous or community governance;
• biosecurity or public-safety risk;
• ongoing legal proceedings; or
• another binding restriction.

The journal may request:

• an anonymised or aggregated version;
• access through a secure environment;
• independent verification by a qualified third party;
• documentation from the data controller;
• a description of the unavailable variables;
• additional methodological reporting; or
• another proportionate means of assessing the results.

35. Data Retention

Authors must retain the data and records necessary to support the published work for the period required by:

• applicable law;
• the authors’ institution;
• the research funder;
• the ethics committee or institutional review board;
• a clinical-trial or regulatory requirement;
• a contractual obligation;
• the repository’s preservation policy; or
• the relevant disciplinary standard.

Where no longer period applies, authors should normally retain supporting research records for at least five years after publication.

Longer retention may be necessary where:

• the research has continuing public-health or regulatory relevance;
• an investigation or legal proceeding is pending;
• the dataset supports multiple publications;
• the research concerns long-term monitoring;
• the data are difficult or impossible to reproduce; or
• another legitimate scholarly reason applies.

36. Changes to Deposited Data

Authors must not silently replace or materially alter a dataset after publication.

Where deposited data require correction or updating:

• a new version should be created;
• the previous version should remain identifiable where possible;
• the nature and date of the change should be documented;
• the persistent identifier or version identifier should be updated;
• the journal should be notified where the change affects the article; and
• a formal correction should be published where necessary.

37. Withdrawal or Removal of Data

Deposited data should not normally be removed merely because the authors no longer wish to share them.

Removal or restricted access may be justified where:

• continued access violates law or participant rights;
• the data contain confidential or personal information disclosed in error;
• the dataset infringes third-party rights;
• continued availability creates a serious safety or security risk;
• the data are fundamentally unreliable or fraudulent;
• a competent authority requires removal; or
• another exceptional and documented reason applies.

Where possible, the repository should retain a metadata record explaining that the dataset has been withdrawn or restricted.

38. Post-Publication Data Requests

Authors must respond professionally and within a reasonable period to legitimate post-publication questions concerning supporting data.

The journal may contact authors where:

• a repository link is inactive;
• the deposited files do not support the reported results;
• the Data Availability Statement is inaccurate;
• access requests are being denied inconsistently;
• the dataset appears incomplete or corrupted;
• an integrity concern has arisen; or
• additional information is necessary to maintain the scholarly record.

39. Failure to Comply

Before publication, failure to comply with this policy may result in:

• a request for a revised Data Availability Statement;
• a requirement to deposit data, code, or materials;
• a request for additional documentation;
• delay of peer review or production;
• additional methodological or integrity review;
• rejection where the findings cannot be evaluated reliably; or
• another proportionate editorial action.

After publication, the journal may:

• request restoration of access;
• publish a correction or clarification;
• update the Data Availability Statement;
• issue an expression of concern;
• investigate possible fabrication, falsification, or misrepresentation;
• contact an institution, funder, repository, ethics committee, or data controller;
• retract the article where the findings are unreliable; or
• take another action under the Publication Ethics Policy.

40. Honest Limitations and Misconduct

An inability to share data because of a legitimate ethical, legal, cultural, contractual, or security restriction is not itself misconduct.

Potential misconduct may arise where an author:

• claims falsely that data are available;
• provides fabricated or substituted data;
• conceals destruction or loss of essential records;
• misrepresents participant consent;
• provides a false access procedure;
• uses confidentiality as a pretext to prevent verification;
• denies access selectively for retaliatory or discriminatory reasons;
• changes the dataset to conceal an error or irregularity;
• shares protected data without authorisation; or
• otherwise misrepresents the provenance, integrity, or availability of the data.

41. Data Loss

If data have been lost, damaged, corrupted, or destroyed, authors must disclose this to the journal promptly.

The explanation should state:

• which data are unavailable;
• when and how the loss occurred;
• whether backups exist;
• whether the reported results can still be verified;
• whether the loss violates a retention obligation;
• what remedial measures were taken; and
• whether an institution or funder has been notified.

Accidental data loss does not automatically establish misconduct, but it may affect publication where the principal findings cannot be evaluated reliably.

42. Recommended Data Availability Statements

Public Repository

The data supporting the findings of this study are available in [repository name] at [DOI or persistent identifier]. The repository record includes [describe data, code, documentation, and relevant materials].

Public Data and Analytical Code

The dataset and analytical code supporting this study are available in [repository name] at [persistent identifier]. The repository includes a data dictionary, analysis scripts, software requirements, and instructions for reproducing the principal results.

Data Included in the Article and Supplementary Material

All data supporting the findings of this study are included in the article and its supplementary materials. Additional clarification may be obtained from the corresponding author where reasonably necessary.

Controlled Access

The participant-level data supporting this study are not publicly available because they contain information subject to privacy and ethical restrictions. Qualified researchers may apply for controlled access through [committee, institution, or repository] at [access location]. Requests will be assessed according to [briefly identify criteria], and an approved data-use agreement is required.

Ethical or Consent Restrictions

The complete dataset cannot be shared publicly because the participant consent and ethics approval do not permit unrestricted secondary use. De-identified aggregated data and supporting documentation are available at [location]. Applications for additional controlled access may be submitted to [responsible body], subject to ethical approval and a data-use agreement.

Third-Party Data

The data analysed in this study were obtained from [data provider] under licence and cannot be redistributed by the authors. Researchers may apply directly to [provider or access portal] under the provider’s standard eligibility and access conditions. The authors did not receive special access unavailable to other qualified applicants.

Commercially Restricted Data

The data supporting this study are subject to a confidentiality agreement with [organisation] and cannot be made publicly available. The authors had complete access to the data necessary for the reported analysis and retained responsibility for interpretation and publication. Requests for controlled access may be directed to [independent committee or data controller], subject to applicable legal and contractual requirements.

Data Available upon Reasonable Request

The data supporting this study are available from the corresponding author upon reasonable request. Public repository deposit is not possible because [specific reason]. Requests from qualified researchers for [permitted purpose] will be considered subject to [ethical approval, confidentiality agreement, or other condition]. Requests will normally receive an initial response within [period].

Qualitative Data

Complete interview transcripts are not publicly available because the detailed narratives could permit participant identification and public sharing was not included in the consent process. The interview guide, coding framework, and de-identified supporting excerpts are available at [repository or supplementary location]. Further controlled access is subject to ethics approval and participant-protection requirements.

Indigenous or Community-Governed Data

The data are governed by [community, authority, or governance body] and are not available for unrestricted public reuse. Access and reuse are subject to community approval, applicable governance protocols, and agreed benefit-sharing conditions. Enquiries may be submitted through [authorised contact or process].

Publicly Available Secondary Data

This study analysed publicly available data obtained from [repository or organisation]. The source datasets are available at [persistent identifiers]. The derived analytical dataset and analysis code are available at [repository identifier].

Systematic Review

The search strategies, screening records, data-extraction forms, extracted data, risk-of-bias assessments, and analysis code supporting this review are available in [repository name] at [persistent identifier]. Copyrighted full-text publications are not redistributed.

No New Data

No new data were generated or analysed for this article. Data availability is therefore not applicable.

No Shareable Data beyond Published Sources

This article is based entirely on publicly available literature and policy documents cited in the reference list. No separate research dataset was generated.

Clinical Trial Data

De-identified individual participant data underlying the reported results, together with the data dictionary, study protocol, statistical analysis plan, and analytic code, will be available from [date] until [date or duration]. Qualified researchers may submit a methodologically sound proposal to [access body]. Approved applicants must enter into a data-use agreement. Further information is available at [registry or repository].

43. Unacceptable Statements

The following statements are not sufficient without further explanation:

• “Data are available.”
• “Data are available upon request.”
• “Data are confidential.”
• “The authors do not wish to share the data.”
• “The data belong to the institution.”
• “Data are available after publication.”
• “Data cannot be shared for privacy reasons.”
• “All relevant data are in the manuscript,” where the underlying results are not actually included.

Authors must identify the relevant data, reason for restriction, responsible access body, and practical access conditions where applicable.

44. Data Management Planning

Authors are encouraged to prepare a data-management plan before collecting or obtaining data.

The plan should consider:

• data types and formats;
• file naming and version control;
• storage and backup;
• security and access controls;
• participant consent;
• ethical and legal requirements;
• third-party rights;
• documentation and metadata;
• repository selection;
• retention and destruction;
• licensing and reuse;
• costs of preservation;
• community or Indigenous governance; and
• responsibility for long-term access.

45. Author Responsibilities

Authors are responsible for:

• ensuring that shared data are accurate and correspond to the article;
• obtaining consent and approval for sharing;
• protecting participants and third parties;
• complying with law, contracts, licences, and governance requirements;
• selecting an appropriate repository;
• preparing adequate metadata and documentation;
• providing a complete Data Availability Statement;
• citing datasets correctly;
• retaining supporting records;
• maintaining controlled-access procedures where promised;
• correcting errors in deposited data;
• responding to legitimate editorial and post-publication enquiries; and
• not overstating the availability or reproducibility of the data.

46. Role of Editors and Reviewers

Editors and reviewers may assess whether:

• the Data Availability Statement is complete and credible;
• the repository and identifier are valid;
• the available data support the reported findings;
• restrictions are justified and proportionate;
• consent and ethical approval permit the proposed sharing;
• the data are documented sufficiently;
• the code and materials are usable;
• commercial or third-party restrictions compromise independent evaluation;
• security or community interests require additional protection; and
• further information is needed before a decision can be made.

Reviewers must treat non-public data as confidential and must not reuse, retain, redistribute, or upload them to unauthorised systems.

47. Editorial Independence

Data-sharing decisions must not be influenced improperly by:

• Article Processing Charges;
• an author’s institutional prestige;
• commercial sponsorship;
• personal or professional relationships;
• anticipated citation or publicity value;
• political pressure;
• publisher preferences unrelated to research integrity; or
• another irrelevant consideration.

Restrictions may be accepted only where they are relevant, credible, proportionate, and compatible with reliable scholarly evaluation.

48. Complaints and Appeals

Authors or data users may request reconsideration where they believe that:

• a data-sharing requirement was applied incorrectly;
• a legitimate ethical, legal, cultural, contractual, or security restriction was not considered;
• access has been denied inconsistently or unfairly;
• a repository or access mechanism has failed;
• an editor or reviewer had an undisclosed conflict of interest;
• material evidence was overlooked; or
• the editorial response was disproportionate.

The request should identify the manuscript, article, or dataset; explain the disputed issue; and provide supporting information.

Further procedures are described in the journal’s Complaints and Appeals Policy.

49. Standards Informing This Policy

This policy is informed by internationally recognised principles concerning research transparency, responsible data sharing, and data governance, including:

• Transparency and Openness Promotion Guidelines;
• FAIR Principles;
• ICMJE Clinical-Trial Data-Sharing Requirements; and
• CARE Principles for Indigenous Data Governance.

Reference to an external organisation means that its guidance informs this policy. It does not imply membership, certification, endorsement, or formal affiliation unless separately stated and independently verifiable.

50. Final Data Availability Checklist

Before submitting a manuscript, authors should confirm that:

• a Data Availability Statement has been included;
• the statement identifies whether data were generated or analysed;
• the data supporting all material results have been identified;
• a suitable repository has been selected where public sharing is possible;
• the dataset has a persistent identifier;
• the repository record can be accessed by editors or reviewers;
• the data correspond to the submitted manuscript;
• data dictionaries and documentation are complete;
• analytical code and software information have been supplied where applicable;
• data formats are accessible and documented;
• the dataset has been cited in PSG Format;
• licensing and reuse terms are clear;
• participant consent permits the proposed sharing;
• privacy and re-identification risks have been assessed;
• ethical, legal, contractual, cultural, commercial, and security restrictions have been addressed;
• controlled-access procedures are specific and operational where required;
• third-party data conditions have been disclosed;
• Indigenous and community data-governance requirements have been respected;
• clinical-trial data-sharing information corresponds to the registry record;
• repository links and identifiers have been tested;
• the authors possess authority to share the deposited materials;
• original research records have been retained;
• no confidential credentials or protected information have been uploaded; and
• all authors have approved the Data Availability Statement.

51. Contact

Questions concerning repository selection, restricted data, controlled access, data citation, consent, commercial confidentiality, Indigenous or community-governed data, clinical-trial data sharing, or post-publication access should be directed to the FSSS Editorial Office through the official contact information provided on the journal website.

Correspondence concerning an existing manuscript, article, or dataset should include:

• the manuscript title;
• the submission identification number or DOI;
• the dataset title;
• the repository and persistent identifier where applicable;
• a clear explanation of the question or restriction;
• the proposed access procedure; and
• any relevant ethical, legal, contractual, governance, or technical documentation.